CPL+: An improved approach for evaluating the local completeness of event logs

• Published in: Information processing letters Vol. 114; no. 11; pp. 607 - 610
• Main Authors: Yang, Hedong, Wen, Lijie, Wang, Jianmin, Wong, Raymond K.
• Format: Journal Article
• Language: English
• Published: Amsterdam Elsevier B.V 01.11.2014; Elsevier Sequoia S.A
• Subjects: Algorithms; Approximation algorithms; Business; Completeness; Criteria; Data mining; Data processing; Event log; Information completeness; Information processing; Logs; Process mining; Programming languages; Studies; Tasks; Process mining; Approximation algorithms; Information completeness; Event log
• ISSN: 0020-0190; 1872-6119
• DOI: 10.1016/j.ipl.2014.06.001

Process mining aims at deriving order relations between tasks recorded by event logs in order to construct their corresponding process models. The quality of the results is not only determined by the mining algorithm being used, but also by the quality of the provided event logs. As a criterion of log quality, completeness measures the magnitude of information for process mining covered by an event log. In this paper, we focus on the evaluation of the local completeness of an event log. In particular, we consider the direct succession (DS) relations between the tasks of a business process. Based on our previous work, an improved approach called CPL+ is proposed in this paper. Experiments show that the proposed CPL+ works better than other approaches, on event logs that contain a small amount of traces. Finally, by further investigating CPL+, we also found that the more distinct DSs observed in an event log, the lower the local completeness of the log is. •We propose an improved approach to estimate the local completeness of event logs.•The approach is analyzed based on a counter-intuitive result that we prove.•Experiments show that the approach is better than other approaches on small logs.